The following references are incorporated in their entirety in the present application: Equity Portfolio Management. Managing Investment Portfolios: A Dynamic Process, Thirds Edition, John L Maginn CFA Donald L. Tuttle CFA, Jerald E. Pinto, CFA, and Dennis W. McLeavey, CFA, editors; U.S. Pat. No. 7,987,130 B2; The Arithmetic of Active Management, William F Sharpe, 1991: http://www.stanford.edu/˜wfsharpe/art/active/active.htm; and The Loser's Game—Charles D Ellis (1975). Financial Analysts Journal, July/August 1975, Vol. 31, No. 4: 19-26. A Relational Model of Data for Large Shared Data Banks, E. F. Codd, 1970: http://www.seas.upenn.edu/˜zives/03f/cis550/codd.pdf.
Note: In the entire discussion, when “traditional” is used to qualify index/sub-index, it refers to market-weighted form of equity index. When it's used to qualify ETF (Exchange Traded Fund), it refers to long-only, passive ETFs. “Index/sub-index” used throughout the discussion is the shortened representation for “equity price index/sub-index”, and is done so for brevity alone. Similarly, “enhanced index” or “enhanced index universe” are used interchangeably in the discussion, as they are one and the same. This discussion pertains only to equity indexes, and therefore, the reference to the word “equity” is dropped as qualifier in many of the references to the word “index”. The word “relational” used in the discussion are synonymous to the word “relational” used by Relational Database Management System (RDBMS) providers like IBM Inc. and Oracle Inc. to describe their database products DB2 and Oracle respectively. It is used with the same connotation as that used by E. F. Codd in describing a RDBMS. The words “non-relational” used in the discussion are antonymous to the word “relational” used by IBM Inc. and Oracle Inc. to describe their database products and by Codd in describing a RDBMS. “Data row identifier” used in the discussion can also be referred to as “row identifier”. The embodiment of the invention discussed here uses only Bloomberg tickers for representing the indexes and sub-indexes, but tickers to represent the same used by data providers like Thomson Reuters, Compustat or Factset may also be used to implement the invention. Types of sub-indexes include and are not limited to—sector sub-indexes, industry group sub-indexes, industry sub-indexes, sub-industry sub-indexes, country sub-indexes, geographical region sub-indexes, economic region sub-indexes, style sub-indexes, market cap sub-indexes and cap-cum-style sub-indexes. The databases Value Factors Database, Enriched Factors Database, Factor Scores Database, Enhanced Index Weights Database and ETF Descriptor Database as described in the invention are non-relational and tabular, and they reside on flat files. However, the qualifiers “non-relational” and “tabular” are excluded in many instances when referring to the databases in the following text for sake of brevity.
The invention ostensibly relates to implementing a linking scheme that ties various disparate non-relational tabular inputs (factors) and staging databases when creating an enhanced equity index and its associated semi-active portfolio. The invention more precisely relates to a technology apparatus and a method for automatic generation of an enhanced equity index (and/or a singular, diversified semi-active equity portfolio) in an economical manner, in terms of cost as well as computer CPU and I/O utilization, from a pre-determined traditional, broad-based equity index universe or benchmark by linking various non-relational tabular databases housing the various inputs and other factors for the enhanced index creation including and not limited to Value Factors Database, Enriched Factors Database, Factor Scores Database, Enhanced Index Weights Database and ETF Descriptor Database using data row identifier constructs. The associated semi-active portfolio based on the enhanced index can be used to create a closed-end fund, a separately managed account, or a unit investment trust. Furthermore, the enhanced index may be used as the basis for creating a passive index tracking fund like an ETF or a mutual fund. The enhanced index or semi-active portfolio may also be used by top-down active portfolio managers as a benchmark or a model portfolio to further enhance and create low-expense active equity portfolios. The semi-active portfolio can be used to fill in gaps and further diversify “complete” active portfolios of stocks, bonds or separately managed accounts in a core-satellite approach, as part of an investor's overall investment profile and diversification strategy.
The invention, while outwardly deploying an automated method to generate an enhanced index, underlines a process and a system that improves database technology for inter-connecting disparate non-relational tabular inputs and staging databases, which are not housed in a Relational Database Management System (RDBMS) like DB2 or Oracle. Automated methods to generate an enhanced index and/or a semi-active portfolio are inherently entrenched in RDBMS like DB2, Oracle or SQL Server. However, the invention sets up a special database scheme that ties disparate inputs and staging tabular databases residing on “flat files”, sourced from different data providers with disparate data formats and disparate update frequencies, in such a manner that the method to automatically construct an enhanced index of a pre-determined type may also be expanded to generate an enhanced indexes repository of all conceivable enhanced indexes made from all conceivable sub-index types underlying all conceivable broad-based index universes/benchmarks using the various embodiments of the method. The invention sets up the enhanced index and the enhanced indexes repository in an optimal manner with reduced computer CPU and I/O utilization. The special database scheme can be seamlessly transferred to create enhanced indexes and the enhanced indexes repository on relational databases housed in a commercially available Relational Database Management System (RDBMS) like DB2 as well.
Flat file databases consist of single or multiple record-type formats, and come in flavors of fixed-length definitions and delimited. The simplest form of flat file is a standard text file and consists of a single record definition. The record or “row” (as commonly referred to) repeats from one to many times, with each successive row representing a common definition. Every row is made up of a horizontal list of fields and the same definition of the row can be applied to every row in the file, and if the fields are constant in length throughout the rows, the file can be deemed as a non-relational tabular database in nature for all purpose. Flat file databases are typically independent of each other or self-contained and therefore, no relationship can be enforced between tabular databases housed on different flat files. They also require no outside architecture to define or store the data for later interpretation. To access the structure of the data in a flat file and manipulate it, the file must be read in its entirety into the computer's memory. Upon completion of the database operations, the file is again written out in its entirety to the host's file system. In this stored mode the database is “flat”, which means it has no structure for indexing and there are usually no structural relationships between the records and as well as between databases. The invention integrates disparate tables on flat file databases with fields (columns) of fixed length and rows of single record definition (one table per flat file) through data row identifier constructs in to an integrated, single (unitary) logical relational database, which follows the integrity rules—entity integrity and referential integrity—that govern commercially available Relational Database Management System (RDBMS) like DB2 or Oracle or SQL Server. Since the data row identifier constructs enforce the integrity rules—entity integrity and referential integrity—, the invention including the method to construct an enhanced index and the enhanced indexes repository can be implemented on RDBMS like DB2 or Oracle. By hosting tabular databases on flat files, SQL (Structure Query Language) need not be used to access individual data rows from tables.
In the broadest sense, equity investment strategies are classified as passive, active, or semi-active. In a passive investing approach, portfolio managers do not react to changes in capital market opportunities in constructing and managing their portfolios. Indexing is the most common approach in passive equity investing, and it refers to holding a basket of securities designed to replicate the returns of a specified index. In contrast, active portfolio managers respond to changing capital market expectations. Active management of a portfolio involves identifying securities, which the portfolio manager thinks will outperform the benchmark, and using them to construct a portfolio. In other words, active portfolio managers attempt to construct a risky portfolio that maximizes the reward-to-variability (Sharpe) ratio. In 1991, William F. Sharpe in his classic article “The Arithmetic of Active Management” argued that average investors cannot hope to beat an equity index. He said, “If active and passive management styles are defined in sensible ways, it must be the case that:                1) before costs, the return on the average actively managed dollar will equal the return on the average passively managed dollar; and        2) after costs, the return on the average actively managed dollar will be less than the return on the average passively managed dollar”Similar sentiments were also expressed by Charles D. Ellis in his 1975 landmark tome “The Loser's Game”, “Gifted, determined, ambitious professionals have come into investment management in such large numbers during the past 30 years that it may no longer be feasible for any of them to profit from the errors of all the others sufficiently often and by sufficient magnitude to beat the market averages”.        
Many historical performance studies have concurred with Sharpe and Ellis, and by and large they have reinforced the notion that the average active institutional portfolio fails to beat the relevant benchmark index in the long-run after adjusting for expenses. Compared to the average actively managed strategy, a well-managed index strategy with similar investment objectives has an edge due to its superior long-term performance, after adjusting for expenses, because of its relatively low portfolio turnover and management fees. Moreover, the low portfolio turnover essentially provides tax efficiency advantages vis-à-vis an active strategy.
In spite of the popularity of indexing, active equity investing still accounts for the overwhelming majority of equity assets managed. Indexing as an investment strategy is optimal in markets with high efficiency. However, in inefficient markets where price discovery has premium, active strategy is endorsed. But higher management fees and higher turnover can eat in to the active returns, i.e., returns in excess of benchmark returns. Higher information gathering expenses prevalent in those markets can make management fees exorbitant and thereby making active strategies unattractive. Falling in between the extremities of passive investing and active investing is the semi-active investing, also known as “enhanced index” or “risk-controlled active” strategy. Semi-active approach is used to design and manage well-diversified equity portfolios that perform better than their benchmark indexes without taking on much additional risk. The portfolio manager creates such a portfolio by making use of his investment perceptions while managing risk characteristics that are incompatible with them. Enhanced index strategies increase the portfolio tracking risk, i.e., variability of active returns, but the higher returns more than compensate for the risk. Semi-active equity investing strategy produces an equity portfolio that has a higher information ratio than that of an equity portfolio derived from an average active equity investing strategy with similar investment objectives, and does so in a cost effective manner. Information ratio is nothing but the mean of the active returns divided by tracking risk, and represents the efficiency of a portfolio's tracking risk in delivering active returns. In other words, semi-active portfolios try to extract active returns like active portfolios, but by keeping their risk as close to the benchmark, they are tracking, like passive portfolios.